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  • Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction

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Basic Science
Original research
Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction

Authors

  • Mohammad Mahdi Shiraz Bhurwani Canon Stroke and Vascular Research Center, Buffalo, New York, USA Biomedical Engineering, University at Buffalo - The State University of New York, Buffalo, New York, USA PubMed articlesGoogle scholar articles
  • Muhammad Waqas Canon Stroke and Vascular Research Center, Buffalo, New York, USA Neurosurgery, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, USA PubMed articlesGoogle scholar articles
  • Alexander R Podgorsak Canon Stroke and Vascular Research Center, Buffalo, New York, USA Biomedical Engineering, University at Buffalo - The State University of New York, Buffalo, New York, USA PubMed articlesGoogle scholar articles
  • Kyle A Williams Canon Stroke and Vascular Research Center, Buffalo, New York, USA Biomedical Engineering, University at Buffalo - The State University of New York, Buffalo, New York, USA PubMed articlesGoogle scholar articles
  • Jason M Davies Canon Stroke and Vascular Research Center, Buffalo, New York, USA Neurosurgery, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, USA Biomedical Informatics, University at Buffalo,The State University of New York, Buffalo, New York, United States PubMed articlesGoogle scholar articles
  • Kenneth Snyder Canon Stroke and Vascular Research Center, Buffalo, New York, USA Neurosurgery, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, USA PubMed articlesGoogle scholar articles
  • Elad Levy Canon Stroke and Vascular Research Center, Buffalo, New York, USA Neurosurgery, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, USA PubMed articlesGoogle scholar articles
  • Adnan Siddiqui Canon Stroke and Vascular Research Center, Buffalo, New York, USA Neurosurgery, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, USA PubMed articlesGoogle scholar articles
  • Ciprian N Ionita Canon Stroke and Vascular Research Center, Buffalo, New York, USA Biomedical Engineering, University at Buffalo - The State University of New York, Buffalo, New York, USA Neurosurgery, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, USA PubMed articlesGoogle scholar articles
  1. Correspondence to Dr Ciprian N Ionita, Biomedical Engineering, University at Buffalo, State University of New York, Buffalo, NY 14203, USA; cnionita{at}buffalo.edu
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Citation

Shiraz Bhurwani MM, Waqas M, Podgorsak AR, et al
Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction
Journal of NeuroInterventional Surgery 2020;12:714-719.

Publication history

  • Received October 14, 2019
  • Revised November 22, 2019
  • Accepted November 24, 2019
  • First published December 10, 2019.
Online issue publication 
June 12, 2020

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© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.